SIGKDD(KDD) 2005 论文列表
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005.
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Pattern-based similarity search for microarray data.
A multinomial clustering model for fast simulation of computer architecture designs.
Short term performance forecasting in enterprise systems.
Mining rare and frequent events in multi-camera surveillance video using self-organizing maps.
Disease progression modeling from historical clinical databases.
Automated detection of frontal systems from numerical model-generated data.
An integrated framework on mining logs files for computing system management.
Mining risk patterns in medical data.
Data mining in the chemical industry.
Generation of synthetic data sets for evaluating the accuracy of knowledge discovery systems.
Failure detection and localization in component based systems by online tracking.
Fast window correlations over uncooperative time series.
CLICKS: an effective algorithm for mining subspace clusters in categorical datasets.
Pattern lattice traversal by selective jumps.
Building connected neighborhood graphs for isometric data embedding.
A generalized framework for mining spatio-temporal patterns in scientific data.
Combining proactive and reactive predictions for data streams.
Formulating distance functions via the kernel trick.
Regression error characteristic surfaces.
Mining comparable bilingual text corpora for cross-language information integration.
A hybrid unsupervised approach for document clustering.
Evaluating similarity measures: a large-scale study in the orkut social network.
Density-based clustering of uncertain data.
Key semantics extraction by dependency tree mining.
Optimizing time series discretization for knowledge discovery.
Efficient computations via scalable sparse kernel partial least squares and boosted latent features.
Estimating missed actual positives using independent classifiers.
Adversarial learning.
Co-clustering by block value decomposition.
A fast kernel-based multilevel algorithm for graph clustering.
Determining an author's native language by mining a text for errors.
Information retrieval based on collaborative filtering with latent interest semantic map.
A maximum entropy web recommendation system: combining collaborative and content features.
Discovering frequent topological structures from graph datasets.
Simultaneous optimization of complex mining tasks with a knowledgeable cache.
Privacy-preserving distributed k-means clustering over arbitrarily partitioned data.
Application of kernels to link analysis.
Maximal boasting.
Unweaving a web of documents.
Creating social networks to improve peer-to-peer networking.
Parallel mining of closed sequential patterns.
LIPED: HMM-based life profiles for adaptive event detection.
Web mining from competitors' websites.
Scalable discovery of hidden emails from large folders.
Integration of profile hidden Markov model output into association rule mining.
Model-based overlapping clustering.
Towards exploratory test instance specific algorithms for high dimensional classification.
Learning to predict train wheel failures.
Enhancing the lift under budget constraints: an application in the mutual fund industry.
Dynamic syslog mining for network failure monitoring.
Email data cleaning.
Modeling and predicting personal information dissemination behavior.
Predicting the product purchase patterns of corporate customers.
A hit-miss model for duplicate detection in the WHO drug safety database.
Using relational knowledge discovery to prevent securities fraud.
Using retrieval measures to assess similarity in mining dynamic web clickstreams.
Making holistic schema matching robust: an ensemble approach.
Deriving marketing intelligence from online discussion.
Price prediction and insurance for online auctions.
An approach to spacecraft anomaly detection problem using kernel feature space.
Finding similar files in large document repositories.
Streaming feature selection using alpha-investing.
A new scheme on privacy-preserving data classification.
Reasoning about sets using redescription mining.
SVM selective sampling for ranking with application to data retrieval.
Cross-relational clustering with user's guidance.
Anonymity-preserving data collection.
Mining closed relational graphs with connectivity constraints.
Summarizing itemset patterns: a profile-based approach.
Improving discriminative sequential learning with rare--but--important associations.
Web object indexing using domain knowledge.
Finding partial orders from unordered 0-1 data.
Probabilistic workflow mining.
Sampling-based sequential subgroup mining.
On the use of linear programming for unsupervised text classification.
Robust boosting and its relation to bagging.
Query chains: learning to rank from implicit feedback.
On mining cross-graph quasi-cliques.
Detection of emerging space-time clusters.
A distributed learning framework for heterogeneous data sources.
Discovering evolutionary theme patterns from text: an exploration of temporal text mining.
A general model for clustering binary data.
Graphs over time: densification laws, shrinking diameters and possible explanations.
Simple and effective visual models for gene expression cancer diagnostics.
Feature bagging for outlier detection.
Combining partitions by probabilistic label aggregation.
A multiple tree algorithm for the efficient association of asteroid observations.
Local sparsity control for naive Bayes with extreme misclassification costs.
Fast discovery of unexpected patterns in data, relative to a Bayesian network.
Nomograms for visualizing support vector machines.
Combining email models for false positive reduction.
Wavelet synopsis for data streams: minimizing non-euclidean error.
The predictive power of online chatter.
Non-redundant clustering with conditional ensembles.
Mining tree queries in a graph.
Dimension induced clustering.
Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering.
Rule extraction from linear support vector machines.
Mining images on semantics via statistical learning.
Variable latent semantic indexing.
A Bayesian network classifier with inverse tree structure for voxelwise magnetic resonance image analysis.
The architecture of complexity: the structure and the dynamics of networks, from the web to the cell.
Mining the internet: the eighth wonder of the world.
Incentive networks.
